Preventing malware pandemics in mobile devices by establishing response-time bounds

The spread of malicious software among computing devices nowadays poses a major threat to the systems' security. Since both the use of mobile devices and the growth of malware's propagation increase rapidly, we are interested in investigating how the time needed by a counter-measure (i.e., an antivirus or a cleaner) to detect and remove a malware from infected devices affects the malware's propagation. In this work, we study the effect of counter-measure's response-time on the propagation of a malicious software and propose a model for establishing reasonable response-time bounds for its activation in order to prevent pandemic. More precisely, given an initial infected population in a network of mobile devices and a specific city area (town's planning), our model establishes upper response-time bounds for a counter-measure which guarantee that, within a period of time, not all the susceptible devices in the city get infected and the infected ones get sanitized. To this end, we first propose a malware propagation model along with a device mobility model, and then we develop a simulator utilizing these models in order to study the spread of malware in such networks. Finally, we present experimental results for the pandemic prevention taken by our simulator for various response-time intervals and other factors that affect the spread deploying different epidemic models.